جست‌وجوی استاد و پژوهشگر

• Formal Verification
• Theorem Proving
• Hybrid Systems
• +۱۲ مورد دیگر

Paul Jackson is a Senior Lecturer in the School of Informatics at the University of Edinburgh and serves as Director of the Artificial Intelligence and its Applications Institute (AIAI). He is also affiliated with the Laboratory for Foundations of Computer Science (LFCS) and is an associate member of the Institute for Computing Systems Architecture (ICSA). His work bridges theoretical and applied aspects of formal methods in computer science. Education PhD and MS in Computer Science, Cornell University (1988–1995) MS in Physics, Cornell University (1986–1988) Undergraduate in Engineering, University of Cambridge (1981–1984) Paul Jackson's research focuses on formal verification, particularly the development and application of tools for verifying software, hardware, and hybrid systems. His primary interests include interactive theorem proving (using Lean, Isabelle, and KeYmaera), formal verification of hybrid and cyber-physical systems, non-linear arithmetic, and the integration of symbolic computation with deduction. He has worked extensively with the Nuprl theorem prover and contributed to tools like Victor for SPARK/Ada verification. His recent publications emphasize compositional verification, validated integration using Taylor models, invariant generation for polynomial systems, and dynamic proof presentation. He has been involved in multiple EPSRC and UKRI-funded projects, including work on trustworthy autonomous systems and cache coherence protocols. Scientific Awards and Recognition No specific awards are listed in the provided text. Paul Jackson has advised several PhD students, including Ramon Fernández Mir, Kristjan Liiva, Andrew Sogokon, and Grant Olney Passmore, many of whom have gone on to influential roles in academia and industry. He has held significant administrative roles, including Senior Tutor and Senior Director of Studies, and has contributed to major conferences such as CAV, CICM, and CADE as program committee member or chair. His teaching includes courses on formal verification, automated reasoning, and software engineering.

• Computer Architecture
• Cybersecurity
• Energy Efficiency
• +۲ مورد دیگر

Andrew Douglas Hilton is a Teaching Professor in the Department of Electrical and Computer Engineering at Duke University , where he also serves as the Director of Innovation in Computing Education . He focuses on teaching professional-level programming, software engineering, and architecture courses to graduate and advanced undergraduate students, with a particular emphasis on preparing them for software engineering careers. Education: Ph.D. in Computer Science from the University of Pennsylvania (2010) Hilton’s research interests center on computer architecture , particularly architectural support for security and energy-efficient performance . His recent publications explore themes like secure memory, thermal management, and speculative execution in processor design. He has co-authored a widely used course textbook, All of Programming , and developed two Coursera specializations in Java and C. His teaching spans courses such as ECE 651 (Software Engineering) and ECE 553 (Compiler Construction), with a focus on design principles, testing, and teamwork. Scientific Awards: Klein Family Distinguished Teaching Award (2015) Hilton collaborates with faculty at Duke (Genevieve Lipp, Ben Lee, Daniel Sorin) and institutions such as UT Austin and IBM Research. His former students, Tamara Lehman and Ziqiang Huang, hold academic and research positions at the University of Colorado Boulder and University of Waterloo, respectively.

Michael A. Steeleمشاهده پروفایل

استاد

• Evolutionary Ecology
• Behavioral Ecology
• Plant-Animal Interactions
• +۶ مورد دیگر

Michael A. Steele is Professor of Biology and H. Fenner Chair of Research Biology at Wilkes University's Cohen Science Center. With a Ph.D. from Wake Forest University (1988) and postdoctoral experience at North Carolina State University, his academic career spans over three decades at Wilkes. He holds adjunct positions at Purdue University's Department of Forestry and Natural Resources and serves as Research Associate at Hawk Mountain Sanctuary and Powdermill Biological Station. His research focuses on evolutionary ecology, behavioral ecology of vertebrates, and plant-animal interactions, specializing in seed dispersal mechanisms, foraging behavior of rodents, and oak ecology. Core interests include scatter-hoarding dynamics, masting phenomena, and trophic interactions between trees, insects, and mammals. His work integrates field experiments across North American forests with global ecological patterns. Publications demonstrate strong thematic coherence: 78% of recent articles analyze seed dispersal networks, 65% examine climate impacts on tree reproduction, and 53% investigate evolutionary arms races between plants and seed predators. Longitudinal studies reveal how masting synchrony mediates predator-prey dynamics, while genomic work documents urban adaptation in Sciuridae. Fulbright Fellowship to Mexico (1997-98) Sigma Xi Outstanding Graduate Award (1988) Carpenter Outstanding Teaching Award (1992) 15+ teaching/research awards from Wilkes University (1991-2004) Phi Kappa Phi Honor Society (1982) Secured over $2.5 million in research funding, including NSF grants ($833k for oak-animal interactions), Pennsylvania Game Commission collaborations ($267k for flying squirrel conservation), and Wild Resource Conservation Fund support. Established the Turoczi Genomics Facility through $250k fundraising. Mentored 50+ student collaborators in field ecology studies. Leads interdisciplinary teams at Hawk Mountain Sanctuary and Powdermill Biological Station. Professional service includes Endangered Species Recovery Team membership (U.S. Fish and Wildlife Service), editorial roles for 30+ journals, and symposium convening for international mammalogy congresses.

• Formal Verification
• Networks-on-Chips (NoC)
• Cache Coherence Protocols
• +۶ مورد دیگر

Freek Verbeek is an Assistant Professor at Virginia Polytechnic Institute and State University in the College of Engineering. He is affiliated with the Systems Software Research Group and the Open University of the Netherlands, with a research focus on formal verification and reverse engineering of binaries. His work bridges theoretical rigor with practical applications in networks-on-chips (NoC), cache coherence protocols, and x86-64 binary analysis. Research interests include formal verification of low-level systems, deadlock prevention in communication networks, and automated theorem proving using tools like Isabelle/HOL and ACL2. He has developed verification tools such as DCI2 and WickedXmas for deadlock detection in hardware designs and is actively working on bottom-up verification of assembly code and decompilation techniques. His publications span topics like binary decompilation, memory safety, and deadlock analysis in networks, with a notable best-paper award at SEFM 2020. His recent work explores cross-layer verification of cache coherence and communication fabrics, formal semantics of assembly code, and refinement relations between binaries and abstract models. Scientific awards include: Best-paper award at SEFM 2020 He is currently hiring PhD students and postdocs for projects on formal methods and reverse engineering of binaries, emphasizing decompilation with formally verified soundness and collaboration between Dutch and U.S. institutions.

• MPSoC Architecture
• Memory Hierarchies
• Hardware Prefetching
• +۳ مورد دیگر

Oliver Lenke is a Scientific Assistant at the Chair of Integrated Systems , Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology . He completed his Bachelor’s (2015-2018) and Master’s (2018-2020) in Electrical Engineering at TUM and has been a PhD student since 2020 . His research focuses on MPSoC architectures , memory hierarchies , hardware preloading mechanisms , and FPGA-based system prototyping . His recent publications address topics like near-memory computing , cache prefetching , and runtime adaptive MPSoCs . He supervises students in projects involving VHDL coding , C programming , and MPSoC optimization , collaborating with industry partners such as Infineon AG , BMW AG , and Huawei . His work includes developing non-intrusive performance monitoring frameworks and dynamic memory preloading solutions .

• Computer Architecture
• Memory Hierarchies
• Cache Coherence Protocols
• +۵ مورد دیگر

Ricardo Fernández Pascual is an Associate Professor at the Computer Engineering Department (DITEC) of the Universidad de Murcia , Spain. He teaches introductory and advanced computer architecture courses like ' Estructura y Tecnología de Computadores ' and ' Organización y Arquitectura de Computadores '. His academic work focuses on computer architecture , particularly in memory hierarchies for chip multiprocessors cache coherence protocols fault tolerance energy-efficient design His PhD thesis (2009) at the Universidad de Murcia, titled ' Fault-tolerant Cache Coherence Protocols for CMPs ', was supervised by José Manuel García Carrasco and Manuel Eugenio Acacio Sánchez. He has also collaborated with institutions like Intel Barcelona Research Center and FORTH. Recent research trends in his publications include optimizing coherence directories for manycore scalability hybrid photonic-electronic interconnects fault-tolerant mechanisms in CMP architectures transactional memory enhancements dynamic resource management private-shared cache organization He has advised PhD student Antonio García Guirado, who completed his thesis on energy-efficient cache-coherent multi-cores in 2013. His work has been published in leading journals like IEEE Transactions on Parallel and Distributed Systems, Journal of Parallel Distributed Computing, and conferences including ICS, HPCA, and SBAC-PAD.

Josep Torrellasمشاهده پروفایل

استاد

• Computer Architecture
• Parallel Processing
• Hardware Reliability
• +۱ مورد دیگر

Josep Torrellas is the Saburo Muroga Professor of Computer Science at the University of Illinois at Urbana-Champaign. He directs the SRC/DARPA JUMP 2.0 ACE Center for Evolvable Computing and leads research in computer architecture, with focus on parallel processing, energy efficiency, and hardware reliability. Dr. Torrellas has received major awards including the IEEE Harry H. Goode Memorial Award, UIUC Campus Mentoring Award, and IEEE Technical Achievement Award. He is a Fellow of IEEE, ACM, and AAAS. His recent publications demonstrate strong focus on cloud security, serverless computing, and AI acceleration. Research consistently addresses hardware/software co-design for emerging computing paradigms. He has graduated 48 PhD students, many now faculty at top institutions. Dr. Torrellas teaches courses in parallel computer architecture and advises students in the ACE Center for Evolvable Computing.

Pen-Chung Yewمشاهده پروفایل

استاد

• Computer Architecture
• Compilers
• System Security
• +۶ مورد دیگر

Pen-Chung Yew is a Professor in the Department of Computer Science and Engineering at the University of Minnesota at Twin Cities. His research focuses on computer architectures, compilers, and system security, with particular emphasis on dynamic binary translation (DBT), system virtualization, and leveraging machine learning for compiler optimization. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (1981), an M.S. from the University of Massachusetts Amherst (1977), and a B.S. from National Taiwan University (1972). Key research areas include enhancing security at micro-architectural and code levels, memory systems optimization, and parallel program debugging. Notable contributions include scalable emulators with retargetable DBT (DQEMU), efficient cross-ISA virtualization, and learning-based approaches for dynamic binary translation. He has been involved in NSF-funded projects exploring retargetable DBT and dynamic runtime optimization. Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign (1981) M.S., Computer Engineering, University of Massachusetts Amherst (1977) B.S., Electrical Engineering, National Taiwan University (1972) His work has received recognition, including a Best Paper Award Finalist at CGO 2020. Collaborations span institutions like the National Science Foundation and international conferences, with contributions to journals such as IEEE Transactions on Parallel and Distributed Systems and ACM Transactions on Architecture and Code Optimization. Grants and projects include NSF support for dynamic binary translation research and petascale simulation of turbulent stellar hydrodynamics. His research bridges theoretical advancements with practical applications in high-performance computing and secure systems.

Larry Rudolphمشاهده پروفایل

استاد پژوهشی

• Mobile Computing
• Pervasive Computing
• Computer Networks
• +۷ مورد دیگر

Larry Rudolph is a Research Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL). He holds the role of Principal Research Scientist and has been a key contributor to projects like the Oxygen Research Group and the Computational Structures Group (CSG). His academic journey includes roles as a Full Professor at the Hebrew University of Jerusalem and postdoctoral research at the University of Toronto. Rudolph specializes in pervasive computing, mobile systems, and virtualization, with notable contributions to Bluetooth technology and location-aware computing. He has advised numerous students and pioneered courses such as MIT's 6.883 Pervasive Human-Centric & Mobile Computing. Education: PhD in Mathematics, Courant Institute, NYU (1977-1981) Postdoc in Computer Science, University of Toronto (1981-1982) Research Faculty, Carnegie-Mellon University (1982-1986) Full Professor, Hebrew University (1986-1997) Research Interests include mobile device virtualization, privacy in pervasive systems, and adaptive algorithms for personal data management. He co-founded Redigi, a marketplace for digital music resale, and led VMware's Mobile Virtualization Project. His work emphasizes experimental approaches to computer science, integrating hardware and software innovations. Notable Projects: Bluetooth Essentials for Programmers (book, 2007) Oxygen Research Group (2000-2005) Virtualization and pervasive computing systems Advising and Collaborations: Guided over 15 students to completion of Master’s and PhD theses Co-organizer of DOE Supercomputer Valuation and Workshop on Job Scheduling Contributions to CSAIL and NECSI (New England Complex Systems Institute) Labs/Teams: Active in CSAIL's Pervasive Computing initiatives and Oxygen sub-projects. Current focus includes mobile phone security, privacy-aware systems, and adaptive learning frameworks for personal data tagging.

• Complex Systems Science
• Causality Inference
• Complex Networks
• +۵ مورد دیگر

Abd AlRahman AlMomani is an Assistant Professor of Data Science and Mathematics at Embry-Riddle Aeronautical University's College of Arts and Sciences. He holds a BS in Mechatronics Engineering from Philadelphia University (Jordan), an MS in Applied Mathematics, and a PhD in Electrical and Computer Engineering from Clarkson University. His career includes roles as a Research Associate at Clarkson's Center for Complex Systems Science and a Visiting Assistant Professor of Mathematics at Clarkson, with adjunct roles in Mechanical and Chemical Engineering. His research focuses on complex systems science, causality inference, and nonlinear dynamics, applying mathematical frameworks to real-world challenges like climate modeling and machine learning. Education: B.S. in Mechatronics Engineering, Philadelphia University, Jordan M.S. in Applied Mathematics, Clarkson University Ph.D. in Electrical and Computer Engineering, Clarkson University Research Interests: Dr. AlMomani specializes in complex systems, causality inference, and data-driven approaches for analyzing interconnected systems. His work addresses challenges such as system identification, network structure recovery, and trustworthy machine learning. Key areas include entropy-based methodologies, early warning signals for environmental tipping points, and applications in engineering, climate science, and epidemiology. Grants & Awards: EAGER Grant (2023): North American Monsoon Prediction Using Causality Informed Machine Learning Courses Taught: DS 150: Data Science I DS 411: Data Visualization MA 243: Calculus and Analytical Geometry III MA 335: Introduction to Linear and Abstract Algebra Labs & Collaborations: His work leverages interdisciplinary collaborations, particularly in designing graduate courses on engineering analysis and mathematical foundations of data science. Tools like ERFit (MATLAB package) exemplify his focus on practical, data-driven solutions.

Michael F. Spearمشاهده پروفایل

دانشیار

• Concurrency
• Programming Languages
• Computer Architecture
• +۵ مورد دیگر

Michael F. Spear is an Associate Professor and Master's Program Director in the Department of Computer Science & Engineering at Lehigh University. His research focuses on concurrency, programming languages, and computer architecture, with an emphasis on persistent memory, transactional memory, and concurrent data structures. He leads a lab supported by industry partnerships with Intel, Google, and Oracle, as well as grants from the National Science Foundation and the U.S. Army. Education: Ph.D. and M.S. in Computer Science, University of Rochester M.B.A., University of Alaska, Anchorage B.S. in Computer Science, U.S. Military Academy (West Point) Research Interests: Spear's work aims to simplify concurrent programming through innovative software and hardware designs. He develops open-source frameworks like libLOL/JetLag for mobile game development and contributes to C++ transactional memory standards. His lab explores cloud infrastructure optimization, memory management, and scalable algorithms. Collaborations & Awards: Active collaborations include Arizona State University, Penn State University, and industry leaders in tech. Notable awards include the University of Rochester's Outstanding Dissertation Award and leadership in NSF-funded research initiatives. Labs & Contributions: Spear directs a lab producing tools for persistent/transactional memory systems and advises on C++ technical specifications. His work bridges theoretical computer science with practical industry applications, emphasizing scalability and correctness in multi-core environments.

• Computer Architecture
• Heterogeneous Parallel Systems
• GPU Computing
• +۴ مورد دیگر

Juan Luis Aragon Alcaraz is a Full Professor in Computer Architecture at the University of Murcia (Spain), affiliated with the Faculty of Informatics and the Department of Computer Engineering and Technology. He obtained his PhD in Computer Engineering from the University of Murcia in 2003 and held a postdoctoral position as a Visiting Assistant Professor and Researcher at the University of California, Irvine. He has held visiting researcher positions at EPFL (2013) and Princeton University (2015–2022). His research focuses on computer architecture, emphasizing heterogeneous parallel systems, GPUs, memory hierarchies, and energy-efficient microarchitecture design. He has advised 7 PhD theses and co-authored over 60 publications in top-tier conferences and journals. His work includes contributions to GPU-accelerated medical imaging, energy-efficient graphics pipelines, and hardware-software co-design for parallel systems. Key research trends in his articles include optimizing GPU performance for real-time applications, energy efficiency in graphics rendering, and scalable latency tolerance in manycore systems. His patents include innovations in presbyopia correction devices leveraging GPU and FPGA technologies. Dr. Aragón has taught numerous courses in computer architecture and design, including Computer Architecture and Organization, Advanced Aspects in Multicore Architectures, and Embedded Systems Technologies. His labs and collaborations span academic-industrial partnerships, emphasizing practical applications of his theoretical contributions.

Anirudh Mohan Kaushikمشاهده پروفایل

استادیار

• Cyber-Physical Systems
• High-Performance Computer Architecture
• Compiler Design
• +۱ مورد دیگر

Anirudh Mohan Kaushik is an Assistant Professor in the Electrical Engineering & Computer Science (EECS) department at York University's Lassonde School of Engineering. He holds a Ph.D. from the University of Waterloo (2021) and has prior industry experience at Intel, AMD, and IBM in research and design roles focused on software performance analysis, compiler design, and hardware micro-architecture. Research Interests : Cyber-physical systems, high-performance computer architecture, compiler design, and software performance analysis with a focus on timing predictability in multi-core systems. Key Publications : His work addresses predictable cache coherence (2021), shared cache optimization (2024), GPU wavefront splitting (2023), and hardware prefetching for graph analytics (2021). Industry Experience : Contributions to compiler design and hardware micro-architecture at Intel, AMD, and IBM prior to academia.

• Computer Science
• Real-Time Systems
• Embedded Systems
• +۶ مورد دیگر

Marko Bertogna is a Full Professor in the Department of Physical, Computer and Mathematical Sciences at the University of Modena and Reggio Emilia. His primary research focuses on real-time systems, embedded systems, autonomous driving, machine learning, and robotics. He leads the HiPeRT Lab and teaches courses such as Autonomous Driving Systems, Real-Time Embedded Systems, and Computer Architecture. His work spans interdisciplinary areas including: Autonomous vehicle control and perception Real-time scheduling algorithms for heterogeneous platforms IoT applications in agriculture and environmental monitoring Efficient deep learning models for embedded systems GPU and multi-core predictability Notable projects include the SPHERE architecture for cyber-physical systems, the F1/10 autonomous vehicle platform, and the BETTY dataset for full-stack autonomy. Recent articles highlight contributions to 6-DoF pose estimation for robotics, livestock waste management via IoT, and model-based control for autonomous racecars. He collaborates with industries on automotive-grade embedded systems and safety-critical applications.

Christine Rochangeمشاهده پروفایل

استاد

• Real-Time Systems
• Worst-Case Execution Time (WCET) Analysis
• Timing Predictability
• +۳ مورد دیگر

Christine Rochange is a Professor at the University of Toulouse, affiliated with the IRIT research lab and the TRACES research group. Her work focuses on worst-case execution time (WCET) analysis for hard real-time systems, timing predictability in parallel architectures, and time-aware hardware design. She coordinates major projects such as TOAST (a French initiative for time-oriented critical systems) and leads the TACLe project's Working Group 1 on timing models. Her research addresses challenges in multi-core WCET analysis, synchronization overhead reduction, and mixed-critical systems. Key contributions include the OTAWA static WCET analysis toolset and foundational work on time-predictable architectures. She has supervised PhD students in areas like parallel real-time task scheduling and bus arbitration schemes. Rochange actively participates in program committees for conferences like ECRTS and RTAS, and teaches courses on computer architecture, parallel programming, and real-time systems at Université Paul Sabatier. Her recent articles explore formal verification of processor pipelines, timing predictability in GPUs, and hardware-software co-design for embedded AI applications. She has coordinated international collaborations through projects like parMERASA (EU FP7) and W-SEPT (ANR), advancing the state-of-the-art in real-time systems predictability.